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  • 51.
    Riliskis, Laurynas
    et al.
    Computer Science Department, Stanford University, 353 Serra Mall, Stanford, CA 94305, USA.
    Osipov, Evgeny
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Symphony: A Framework for Accurate and Holistic WSN Simulation2015In: Sensors, E-ISSN 1424-8220, Vol. 15, no 3, p. 4677-4699Article in journal (Refereed)
    Abstract [en]

    Research on wireless sensor networks has progressed rapidly over the last decade, and these technologies have been widely adopted for both industrial and domestic uses. Several operating systems have been developed, along with a multitude of network protocols for all layers of the communication stack. Industrial Wireless Sensor Network (WSN) systems must satisfy strict criteria and are typically more complex and larger in scale than domestic systems. Together with the non-deterministic behavior of network hardware in real settings, this greatly complicates the debugging and testing of WSN functionality. To facilitate the testing, validation, and debugging of large-scale WSN systems, we have developed a simulation framework that accurately reproduces the processes that occur inside real equipment, including both hardware- and software-induced delays. The core of the framework consists of a virtualized operating system and an emulated hardware platform that is integrated with the general purpose network simulator ns-3. Our framework enables the user to adjust the real code base as would be done in real deployments and also to test the boundary effects of different hardware components on the performance of distributed applications and protocols. Additionally we have developed a clock emulator with several different skew models and a component that handles sensory data feeds. The new framework should substantially shorten WSN application development cycles.

  • 52.
    Saad Shaikh, Muhammad
    et al.
    Department of Electronics Design, Mid Sweden University, 851 70 Sundsvall, Sweden.
    Jaferzadeh, Keyvan
    Department of Electronics Design, Mid Sweden University, 851 70 Sundsvall, Sweden; Department of Computer Science and Software Engineering, Concordia University, Montreal, QC H3G 1M8, Canada.
    Thörnberg, Benny
    Department of Electronics Design, Mid Sweden University, 851 70 Sundsvall, Sweden.
    Casselgren, Johan
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Calibration of a Hyper-Spectral Imaging System Using a Low-Cost Reference2021In: Sensors, E-ISSN 1424-8220, Vol. 21, no 11, article id 3738Article in journal (Refereed)
    Abstract [en]

    In this paper, we present a hyper-spectral imaging system and practical calibration procedure using a low-cost calibration reference made of polytetrafluoroethylene. The imaging system includes a hyperspectral camera and an active source of illumination with a variable spectral distribution of intensity. The calibration reference is used to measure the relative reflectance of any material surface independent of the spectral distribution of light and camera sensitivity. Winter road conditions are taken as a test application, and several spectral images of snow, icy asphalt, dry asphalt, and wet asphalt were made at different exposure times using different illumination spectra. Graphs showing measured relative reflectance for different road conditions support the conclusion that measurements are independent of illumination. Principal component analysis of the acquired spectral data for road conditions shows well separated data clusters, demonstrating the system’s suitability for material classification.

  • 53.
    Sagar, Atish
    et al.
    Division of Agricultural Engineering, ICAR—Indian Agriculture Research Institute, New Delhi 110012, India.
    Hasan, Murtaza
    Centre for Protected Cultivation Technology, ICAR—Indian Agriculture Research Institute, New Delhi 110012, India.
    Singh, Dhirendra Kumar
    Division of Agricultural Engineering, ICAR—Indian Agriculture Research Institute, New Delhi 110012, India.
    Al-Ansari, Nadhir
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Chakraborty, Debashis
    Division of Agricultural Physics, ICAR—Indian Agriculture Research Institute, New Delhi 110012, India.
    Singh, Mam Chand
    Centre for Protected Cultivation Technology, ICAR—Indian Agriculture Research Institute, New Delhi 110012, India.
    Iquebal, Mir Asif
    Indian Agricultural Statistics Research Institute, Indian Council of Agricultural Research, New Delhi 110012, India.
    Kumar, Amit
    Division of Agricultural Engineering, ICAR—Indian Agriculture Research Institute, New Delhi 110012, India.
    Malkani, Pankaj
    Division of Agricultural Engineering, ICAR—Indian Agriculture Research Institute, New Delhi 110012, India.
    Vishwakarma, Dinesh Kumar
    Department of Irrigation and Drainage Engineering, G. B. Pant, University of Agriculture and Technology, Pantnagar 263145, India.
    Elbeltagi, Ahmed
    Agricultural Engineering Department, Faculty of Agriculture, Mansoura University, Mansoura 35516, Egypt.
    Development of Smart Weighing Lysimeter for Measuring Evapotranspiration and Developing Crop Coefficient for Greenhouse Chrysanthemum2022In: Sensors, E-ISSN 1424-8220, Vol. 22, no 16, article id 6239Article in journal (Refereed)
    Abstract [en]

    The management of water resources is a priority problem in agriculture, especially in areas with a limited water supply. The determination of crop water requirements and crop coefficient (Kc) of agricultural crops helps to create an appropriate irrigation schedule for the effective management of irrigation water. A portable smart weighing lysimeter (1000 × 1000 mm and 600 mm depth) was developed at CPCT, IARI, New Delhi for real-time measurement of Crop Coefficient (Kc) and water requirement of chrysanthemum crop and bulk data storage. The paper discusses the assembly, structural and operational design of the portable smart weighting lysimeter. The performance characteristics of the developed lysimeter were evaluated under different load conditions. The Kc values of the chrysanthemum crop obtained from the lysimeter installed inside the greenhouse were Kc ini. 0.43 and 0.38, Kc mid-1.27 and 1.25, and Kc end-0.67 and 0.59 for the years 2019–2020 and 2020–2021, respectively, which apprehensively corroborated with the FAO 56 paper for determination of crop coefficient. The Kc values decreased progressively at the late-season stage because of the maturity and aging of the leaves. The lysimeter’s edge temperature was somewhat higher, whereas the center temperature closely matched the field temperature. The temperature difference between the center and the edge increased as the ambient temperature rose. The developed smart lysimeter system has unique applications due to its real-time measurement, portable attribute, and ability to produce accurate results for determining crop water use and crop coefficient for greenhouse chrysanthemum crops.

  • 54.
    Sanchez-Comas, Andres
    et al.
    Department of Productivity and Innovation, Universidad de la Costa, Barranquilla 080 002, Colombia.
    Synnes, Kåre
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hallberg, Josef
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies2020In: Sensors, E-ISSN 1424-8220, Vol. 20, no 15, article id 4227Article, review/survey (Refereed)
    Abstract [en]

    Activity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching even the people most in need. This study was strongly motivated because levels of development, deployment, and technology of AR solutions transferred to society and industry are based on software development, but also depend on the hardware devices used. The current paper identifies contributions to hardware uses for activity recognition through a scientific literature review in the Web of Science (WoS) database. This work found four dominant groups of technologies used for AR in SH and AAL—smartphones, wearables, video, and electronic components—and two emerging technologies: Wi-Fi and assistive robots. Many of these technologies overlap across many research works. Through bibliometric networks analysis, the present review identified some gaps and new potential combinations of technologies for advances in this emerging worldwide field and their uses. The review also relates the use of these six technologies in health conditions, health care, emotion recognition, occupancy, mobility, posture recognition, localization, fall detection, and generic activity recognition applications. The above can serve as a road map that allows readers to execute approachable projects and deploy applications in different socioeconomic contexts, and the possibility to establish networks with the community involved in this topic. This analysis shows that the research field in activity recognition accepts that specific goals cannot be achieved using one single hardware technology, but can be using joint solutions, this paper shows how such technology works in this regard.

  • 55.
    Sanchez-Comas, Andres
    et al.
    Department of Productivity and Innovation, Universidad de la Costa, 080 002 Barranquilla, Colombia.
    Synnes, Kåre
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Molina-Estren, Diego
    Department of Computer Science and Electronics, Universidad de la Costa, 080 002 Barranquilla, Colombia.
    Troncoso-Palacio, Alexander
    Department of Productivity and Innovation, Universidad de la Costa, 080 002 Barranquilla, Colombia.
    Comas-González, Zhoe
    Department of Computer Science and Electronics, Universidad de la Costa, 080 002 Barranquilla, Colombia.
    Correlation Analysis of Different Measurement Places of Galvanic Skin Response in Test Groups Facing Pleasant and Unpleasant Stimuli2021In: Sensors, E-ISSN 1424-8220, Vol. 21, no 12, article id 4210Article in journal (Refereed)
    Abstract [en]

    The galvanic skin response (GSR; also widely known as electrodermal activity (EDA)) is a signal for stress-related studies. Given the sparsity of studies related to the GSR and the variety of devices, this study was conducted at the Human Health Activity Laboratory (H2AL) with 17 healthy subjects to determine the variability in the detection of changes in the galvanic skin response among a test group with heterogeneous respondents facing pleasant and unpleasant stimuli, correlating the GSR biosignals measured from different body sites. We experimented with the right and left wrist, left fingers, the inner side of the right foot using Shimmer3GSR and Empatica E4 sensors. The results indicated the most promising homogeneous places for measuring the GSR, namely, the left fingers and right foot. The results also suggested that due to a significantly strong correlation among the inner side of the right foot and the left fingers, as well as the moderate correlations with the right and left wrists, the foot may be a suitable place to homogenously measure a GSR signal in a test group. We also discuss some possible causes of weak and negative correlations from anomalies detected in the raw data possibly related to the sensors or the test group, which may be considered to develop robust emotion detection systems based on GRS biosignals.

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  • 56.
    Sebastián, Eduardo M.
    et al.
    Centro de Astrobiología (CSIC-INTA), Torrejõn de Ardoz, Madrid.
    Armiens, Carlos
    Centro de Astrobiología (CSIC-INTA), Torrejõn de Ardoz, Madrid.
    Gõmez-Elvira, Javier
    Centro de Astrobiología (CSIC-INTA), Torrejõn de Ardoz, Madrid.
    Zorzano, María Paz
    Centro de Astrobiología (CSIC-INTA).
    Martínez-Frías, Jesús
    Centro de Astrobiología (CSIC-INTA), Torrejõn de Ardoz, Madrid.
    Esteban, Blanca
    Department of Physics, University of Alcalá.
    Ramos, Miguel A.
    Department of Physics, University of Alcalá.
    The rover environmental monitoring station ground temperature sensor: A pyrometer for measuring ground temperature on mars2010In: Sensors, E-ISSN 1424-8220, Vol. 10, no 10, p. 9211-9231Article in journal (Refereed)
    Abstract [en]

    We describe the parameters that drive the design and modeling of the Rover Environmental Monitoring Station (REMS) Ground Temperature Sensor (GTS), an instrument aboard NASA's Mars Science Laboratory, and report preliminary test results. REMS GTS is a lightweight, low-power, and low cost pyrometer for measuring the Martian surface kinematic temperature. The sensor's main feature is its innovative design, based on a simple mechanical structure with no moving parts. It includes an in-flight calibration system that permits sensor recalibration when sensor sensitivity has been degraded by deposition of dust over the optics. This paper provides the first results of a GTS engineering model working in a Martian-like, extreme environment

  • 57.
    Seo, Jungryul
    et al.
    Department of Computer Engineering, Ajou University, Suwon, Korea.
    Laine, Teemu H.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Sohn, Kyung-Ah
    Department of Computer Engineering, Ajou University, Suwon, Korea.
    An Exploration of Machine Learning Methods for Robust Boredom Classification Using EEG and GSR Data2019In: Sensors, E-ISSN 1424-8220, Vol. 19, no 20, article id 4561Article in journal (Refereed)
    Abstract [en]

    In recent years, affective computing has been actively researched to provide a higher level of emotion-awareness. Numerous studies have been conducted to detect the user’s emotions from physiological data. Among a myriad of target emotions, boredom, in particular, has been suggested to cause not only medical issues but also challenges in various facets of daily life. However, to the best of our knowledge, no previous studies have used electroencephalography (EEG) and galvanic skin response (GSR) together for boredom classification, although these data have potential features for emotion classification. To investigate the combined effect of these features on boredom classification, we collected EEG and GSR data from 28 participants using off-the-shelf sensors. During data acquisition, we used a set of stimuli comprising a video clip designed to elicit boredom and two other video clips of entertaining content. The collected samples were labeled based on the participants’ questionnaire-based testimonies on experienced boredom levels. Using the collected data, we initially trained 30 models with 19 machine learning algorithms and selected the top three candidate classifiers. After tuning the hyperparameters, we validated the final models through 1000 iterations of 10-fold cross validation to increase the robustness of the test results. Our results indicated that a Multilayer Perceptron model performed the best with a mean accuracy of 79.98% (AUC: 0.781). It also revealed the correlation between boredom and the combined features of EEG and GSR. These results can be useful for building accurate affective computing systems and understanding the physiological properties of boredom.

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  • 58.
    Shitiri, Ethungshan
    et al.
    School of Electronics, Kyungpook National University, Korea.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Cho, Ho-Shin
    School of Electronics, Kyungpook National University, Korea.
    Biological Oscillators in Nanonetworks-Opportunities and Challenges2018In: Sensors, E-ISSN 1424-8220, Vol. 18, no 5, article id 1544Article in journal (Refereed)
    Abstract [en]

    One of the major issues in molecular communication-based nanonetworks is the provision and maintenance of a common time knowledge. To stay true to the definition of molecular communication, biological oscillators are the potential solutions to achieve that goal as they generate oscillations through periodic fluctuations in the concentrations of molecules. Through the lens of a communication systems engineer, the scope of this survey is to explicitly classify, for the first time, existing biological oscillators based on whether they are found in nature or not, to discuss, in a tutorial fashion, the main principles that govern the oscillations in each oscillator, and to analyze oscillator parameters that are most relevant to communication engineer researchers. In addition, the survey highlights and addresses the key open research issues pertaining to several physical aspects of the oscillators and the adoption and implementation of the oscillators to nanonetworks. Moreover, key research directions are discussed.

  • 59.
    Soltani Dehkharqani, Arash
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Engström, Fredrik
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Aidanpää, Jan-Olov
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Cervantes, Michel
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    An Indirect Measurement Methodology to Identify Load Fluctuations on Axial Turbine Runner Blades2020In: Sensors, E-ISSN 1424-8220, Vol. 20, no 24, article id 7220Article in journal (Refereed)
    Abstract [en]

    Smooth integration of intermittent energy sources, such as solar and wind power, into the electrical grid induces new operating conditions of the hydraulic turbine by increasing the off-design operations, start/stops, and load variations. Therefore, hydraulic turbines are subject to unstable flow conditions and unfavorable load fluctuations. Predicting load fluctuations on the runner using indirect measurements can allow for optimized operations of the turbine units, increase turbine refurbishment time intervals, and avoid structural failures in extreme cases. This paper investigates an experimental methodology to assess and predict the flow condition and load fluctuations on a Kaplan turbine runner at several steady-state operations by performing measurements on the shaft in the rotating and stationary frame of references. This unit is instrumented with several transducers such as miniature pressure transducers, strain gages, and proximity probes. The results show that for any propeller curve of a Kaplan turbine, the guide vane opening corresponding to the minimum pressure and strain fluctuations on the runner blade can be obtained by axial, torsion, and bending measurements on the shaft. Torsion measurements on the shaft could support index-testing in Kaplan turbines particularly for updating the cam-curve during the unit operation. Furthermore, a signature of every phenomenon observed on the runner blade signals, e.g., runner frequency, rotating vortex rope components, and rotor-stator interaction, is found in the data obtained from the shaft.

  • 60.
    Stöggl, Thomas
    et al.
    Mittuniversitetet, Avdelningen för hälsovetenskap.
    Holst, Anders
    School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden .
    Jonasson, Arndt
    Swedish Institute of Computer Science, Kista, Sweden.
    Andersson, Erik
    Mittuniversitetet, Avdelningen för hälsovetenskap.
    Wunsch, Thomas
    Department of Sport Science and Kinesiology, University of SalzburgHallein/Rif, Austria .
    Norström, Christer
    Swedish Institute of Computer Science, Kista, Sweden .
    Holmberg, Hans-Christer
    Mittuniversitetet, Avdelningen för hälsovetenskap.
    Automatic classification of the sub-techniques (gears) used in cross-country ski skating employing a mobile phone2014In: Sensors, E-ISSN 1424-8220, Vol. 14, no 11, p. 20589-20601Article in journal (Refereed)
    Abstract [en]

    The purpose of the current study was to develop and validate an automatic algorithm for classification of cross-country (XC) ski-skating gears (G) using Smartphone accelerometer data. Eleven XC skiers (seven men, four women) with regional-to-international levels of performance carried out roller skiing trials on a treadmill using fixed gears (G2left, G2right, G3, G4left, G4right) and a 950-m trial using different speeds and inclines, applying gears and sides as they normally would. Gear classification by the Smartphone (on the chest) and based on video recordings were compared. Formachine-learning, a collective database was compared to individual data. The Smartphone application identified the trials with fixed gears correctly in all cases. In the 950-m trial, participants executed 140 ± 22 cycles as assessed by video analysis, with the automatic Smartphone application giving a similar value. Based on collective data, gears were identified correctly 86.0% ± 8.9% of the time, a value that rose to 90.3% ± 4.1% (P < 0.01) with machine learning from individual data. Classification was most often incorrect during transition between gears, especially to or from G3. Identification was most often correct for skiers who made relatively few transitions between gears. The accuracy of the automatic procedure for identifying G2left, G2right, G3, G4left and G4right was 96%, 90%, 81%, 88% and 94%, respectively. The algorithm identified gears correctly 100% of the time when a single gear was used and 90% of the time when different gears were employed during a variable protocol. This algorithm could be improved with respect to identification of transitions between gears or the side employed within a given gear.

  • 61.
    Sumanasena, Vidura
    et al.
    Research Centre for Data Analytics and Cognition, La Trobe University, Bundoora, VIC, 3083, Australia.
    Fernando, Heshan
    Department of Computer Engineering, Rensselaer Polytechnic Institute, New York, NY 12180, USA.
    De Silva, Daswin
    Research Centre for Data Analytics and Cognition, La Trobe University, Bundoora, VIC, 3083, Australia.
    Thileepan, Beniel
    Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK.
    Pasan, Amila
    Centre for Wireless Communications, University of Oulu, 90570 Oulu, Finland.
    Samarawickrama, Jayathu
    Department of Electronic and Telecom Engineering, University of Moratuwa, Moratuwa, 10400, Sri Lanka.
    Osipov, Evgeny
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Alahakoon, Damminda
    Research Centre for Data Analytics and Cognition, La Trobe University, Bundoora, VIC, 3083, Australia.
    Hardware Efficient Direct Policy Imitation Learning for Robotic Navigation in Resource-Constrained Settings2024In: Sensors, E-ISSN 1424-8220, Vol. 24, no 1, article id 185Article in journal (Refereed)
    Abstract [en]

    Direct policy learning (DPL) is a widely used approach in imitation learning for time-efficient and effective convergence when training mobile robots. However, using DPL in real-world applications is not sufficiently explored due to the inherent challenges of mobilizing direct human expertise and the difficulty of measuring comparative performance. Furthermore, autonomous systems are often resource-constrained, thereby limiting the potential application and implementation of highly effective deep learning models. In this work, we present a lightweight DPL-based approach to train mobile robots in navigational tasks. We integrated a safety policy alongside the navigational policy to safeguard the robot and the environment. The approach was evaluated in simulations and real-world settings and compared with recent work in this space. The results of these experiments and the efficient transfer from simulations to real-world settings demonstrate that our approach has improved performance compared to its hardware-intensive counterparts. We show that using the proposed methodology, the training agent achieves closer performance to the expert within the first 15 training iterations in simulation and real-world settings.

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  • 62.
    Usman, Muhammad
    et al.
    Department of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Chiniot-Faisalabad Campus, Chiniot 35400, Pakistan.
    Sarfraz, Muhammad Shahzad
    Department of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Chiniot-Faisalabad Campus, Chiniot 35400, Pakistan.
    Habib, Usman
    AI and Data Science Department, FAST School of Computing, National University of Computer and Emerging Sciences, Islamabad, Islamabad Campus, Islamabad 44000, Pakistan.
    Aftab, Muhammad Umar
    Department of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Chiniot-Faisalabad Campus, Chiniot 35400, Pakistan.
    Javed, Saleha
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Automatic Hybrid Access Control in SCADA-Enabled IIoT Networks Using Machine Learning2023In: Sensors, E-ISSN 1424-8220, Vol. 23, no 8, article id 3931Article in journal (Refereed)
    Abstract [en]

    The recent advancements in the Internet of Things have made it converge towards critical infrastructure automation, opening a new paradigm referred to as the Industrial Internet of Things (IIoT). In the IIoT, different connected devices can send huge amounts of data to other devices back and forth for a better decision-making process. In such use cases, the role of supervisory control and data acquisition (SCADA) has been studied by many researchers in recent years for robust supervisory control management. Nevertheless, for better sustainability of these applications, reliable data exchange is crucial in this domain. To ensure the privacy and integrity of the data shared between the connected devices, access control can be used as the front-line security mechanism for these systems. However, the role engineering and assignment propagation in access control is still a tedious process as its manually performed by network administrators. In this study, we explored the potential of supervised machine learning to automate role engineering for fine-grained access control in Industrial Internet of Things (IIoT) settings. We propose a mapping framework to employ a fine-tuned multilayer feedforward artificial neural network (ANN) and extreme learning machine (ELM) for role engineering in the SCADA-enabled IIoT environment to ensure privacy and user access rights to resources. For the application of machine learning, a thorough comparison between these two algorithms is also presented in terms of their effectiveness and performance. Extensive experiments demonstrated the significant performance of the proposed scheme, which is promising for future research to automate the role assignment in the IIoT domain.

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  • 63.
    Vakkada Ramachandran, Abhilash
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Israel Nazarious, Miracle
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Mathanlal, Thasshwin
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Zorzano, María-Paz
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology. Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, 28850 Madrid, Spain. School of Geosciences, University of Aberdeen, Aberdeen, AB24 3FX, UK.
    Martin-Torres, Javier
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology. School of Geosciences, University of Aberdeen, Aberdeen, AB24 3FX, UK. Instituto Andaluz de Ciencias de la Tierra (CSIC-UGR), 18100 Granada, Spain.
    Space Environmental Chamber for Planetary Studies2020In: Sensors, E-ISSN 1424-8220, Vol. 20, no 14, article id 3996Article in journal (Refereed)
    Abstract [en]

    We describe a versatile simulation chamber that operates under representative space conditions (pressures from < 10−5 mbar to ambient and temperatures from 163 to 423 K), the SpaceQ chamber. This chamber allows to test instrumentation, procedures, and materials and evaluate their performance when exposed to outgassing, thermal vacuum, low temperatures, baking, dry heat microbial reduction (DHMR) sterilization protocols, and water. The SpaceQ is a cubical stainless-steel chamber of 27,000 cm3 with a door of aluminum. The chamber has a table which can be cooled using liquid nitrogen. The chamber walls can be heated (for outgassing, thermal vacuum, or dry heat applications) using an outer jacket. The chamber walls include two viewports and 12 utility ports (KF, CF, and Swagelok connectors). It has sensors for temperature, relative humidity, and pressure, a UV–VIS–NIR spectrometer, a UV irradiation lamp that operates within the chamber as well as a stainless-steel syringe for water vapor injection, and USB, DB-25 ports to read the data from the instruments while being tested inside. This facility has been specifically designed for investigating the effect of water on the Martian surface. The core novelties of this chamber are: (1) its ability to simulate the Martian near-surface water cycle by injecting water multiple times into the chamber through a syringe which allows to control and monitor precisely the initial relative humidity inside with a sensor that can operate from vacuum to Martian pressures and (2) the availability of a high-intensity UV lamp, operating from vacuum to Martian pressures, within the chamber, which can be used to test material curation, the role of the production of atmospheric radicals, and the degradation of certain products like polymers and organics. For illustration, here we present some applications of the SpaceQ chamber at simulated Martian conditions with and without atmospheric water to (i) calibrate the ground temperature sensor of the Engineering Qualification Model of HABIT (HabitAbility: Brines, Irradiation and Temperature) instrument, which is a part of ExoMars 2022 mission. These tests demonstrate that the overall accuracy of the temperature retrieval at a temperature between −50 and 10 °C is within 1.3 °C and (ii) investigate the curation of composite materials of Martian soil simulant and binders, with added water, under Martian surface conditions under dry and humid conditions. Our studies have demonstrated that the regolith, when mixed with super absorbent polymer (SAP), water, and binders exposed to Martian conditions, can form a solid block and retain more than 80% of the added water, which may be of interest to screen radiation while maintaining a low weight. 

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  • 64.
    Vakkada Ramachandran, Abhilash
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Zorzano Mier, María-Paz
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology. Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, 28850 Madrid, Spain; School of Geosciences, University of Aberdeen, Aberdeen AB24 3FX, UK .
    Martín-Torres, Javier
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology. Centro de Astrobiología (CSIC-INTA), Torrejón de Ardoz, 28850 Madrid, Spain; School of Geosciences, University of Aberdeen, Aberdeen AB24 3FX, UK .
    Experimental Investigation of the Atmosphere-Regolith Water Cycle on Present-Day Mars2021In: Sensors, E-ISSN 1424-8220, Vol. 21, no 21, article id 7421Article in journal (Refereed)
    Abstract [en]

    The water content of the upper layers of the surface of Mars is not yet quantified. Laboratory simulations are the only feasible way to investigate this in a controlled way on Earth, and then compare it with remote and in situ observations of spacecrafts on Mars. Describing the processes that may induce changes in the water content of the surface is critical to determine the present-day habitability of the Martian surface, to understand the atmospheric water cycle, and to estimate the efficiency of future water extraction procedures from the regolith for In Situ Resource Utilization (ISRU). This paper illustrates the application of the SpaceQ facility to simulate the near-surface water cycle under Martian conditions. Rover Environmental Monitoring Station (REMS) observations at Gale crater show a non-equilibrium situation in the atmospheric H2O volume mixing ratio (VMR) at night-time, and there is a decrease in the atmospheric water content by up to 15 g/m2 within a few hours. This reduction suggests that the ground may act at night as a cold sink scavenging atmospheric water. Here, we use an experimental approach to investigate the thermodynamic and kinetics of water exchange between the atmosphere, a non-porous surface (LN2-chilled metal), various salts, Martian regolith simulant, and mixtures of salts and simulant within an environment which is close to saturation. We have conducted three experiments: the stability of pure liquid water around the vicinity of the triple point is studied in experiment 1, as well as observing the interchange of water between the atmosphere and the salts when the surface is saturated; in experiment 2, the salts were mixed with Mojave Martian Simulant (MMS) to observe changes in the texture of the regolith caused by the interaction with hydrates and liquid brines, and to quantify the potential of the Martian regolith to absorb and retain water; and experiment 3 investigates the evaporation of pure liquid water away from the triple point temperature when both the air and ground are at the same temperature and the relative humidity is near saturation. We show experimentally that frost can form spontaneously on a surface when saturation is reached and that, when the temperature is above 273.15 K (0 °C), this frost can transform into liquid water, which can persist for up to 3.5 to 4.5 h at Martian surface conditions. For comparison, we study the behavior of certain deliquescent salts that exist on the Martian surface, which can increase their mass between 32% and 85% by absorption of atmospheric water within a few hours. A mixture of these salts in a 10% concentration with simulant produces an aggregated granular structure with a water gain of approximately 18- to 50-wt%. Up to 53% of the atmospheric water was captured by the simulated ground, as pure liquid water, hydrate, or brine.

  • 65.
    Verdel, Nina
    et al.
    Department of Health Sciences, Mid Sweden University, 83125 Östersund, Sweden; Faculty of Sport, University of Ljubljana, 1000 Ljubljana, Slovenia.
    Drobnič, Miha
    Faculty of Sport, University of Ljubljana, 1000 Ljubljana, Slovenia.
    Maslik, Jan
    Department of Materials Science and Engineering, Uppsala University, 75121 Uppsala, Sweden.
    Björnander Rahimi, Klara
    Department of Materials Science and Engineering, Uppsala University, 75121 Uppsala, Sweden.
    Tantillo, Giorgio
    STMicroelectronics, 20864 Agrate Brianza, Italy.
    Gumiero, Alessandro
    STMicroelectronics, 20864 Agrate Brianza, Italy.
    Hjort, Klas
    Department of Materials Science and Engineering, Uppsala University, 75121 Uppsala, Sweden.
    Holmberg, Hans-Christer
    Luleå University of Technology, Department of Health, Learning and Technology, Health, Medicine and Rehabilitation. Department of Physiology and Pharmacology, Karolinska Institutet, 17177 Stockholm, Sweden.
    Supej, Matej
    Department of Health Sciences, Mid Sweden University, 83125 Östersund, Sweden; Faculty of Sport, University of Ljubljana, 1000 Ljubljana, Slovenia.
    A Comparison of a Novel Stretchable Smart Patch for Measuring Runner’s Step Rates with Existing Measuring Technologies2022In: Sensors, E-ISSN 1424-8220, Vol. 22, no 13, article id 4897Article in journal (Refereed)
    Abstract [en]

    A novel wearable smart patch can monitor various aspects of physical activity, including the dynamics of running, but like any new device developed for such applications, it must first be tested for validity. Here, we compare the step rate while running in place as measured by this smart patch to the corresponding values obtained utilizing ‘‘gold standard’’ MEMS accelerometers in combination with bilateral force plates equipped with HBM load cells, as well as the values provided by a three-dimensional motion capture system and the Garmin Dynamics Running Pod. The 15 healthy, physically active volunteers (age = 23 ± 3 years; body mass = 74 ± 17 kg, height = 176 ± 10 cm) completed three consecutive 20-s bouts of running in place, starting at low, followed by medium, and finally at high intensity, all self-chosen. Our major findings are that the rates of running in place provided by all four systems were valid, with the notable exception of the fast step rate as measured by the Garmin Running Pod. The lowest mean bias and LoA for these measurements at all rates were associated consistently with the smart patch. 

  • 66.
    Verdel, Nina
    et al.
    Swedish Winter Sports Research Centre, Mid Sweden University, 83125 Östersund, Sweden.
    Podlogar, Tim
    Faculty of Health Sciences, University of Primorska, 6310 Izola, Slovenia; Department of Automation, Biocybernetics, and Robotics, Jozef Stefan Institute, 1000 Ljubljana, Slovenia; Human Performance Centre, 1000 Ljubljana, Slovenia.
    Ciuha, Urša
    Department of Automation, Biocybernetics, and Robotics, Jozef Stefan Institute, 1000 Ljubljana, Slovenia.
    Holmberg, Hans-Christer
    Luleå University of Technology, Department of Health, Learning and Technology, Health, Medicine and Rehabilitation.
    Debevec, Tadej
    Department of Automation, Biocybernetics, and Robotics, Jozef Stefan Institute, 1000 Ljubljana, Slovenia; Faculty of Sport, University of Ljubljana, 1000 Ljubljana, Slovenia.
    Supej, Matej
    Swedish Winter Sports Research Centre, Mid Sweden University, 83125 Östersund, Sweden; Faculty of Sport, University of Ljubljana, 1000 Ljubljana, Slovenia.
    Reliability and Validity of the CORE Sensor to Assess Core Body Temperature during Cycling Exercise2021In: Sensors, E-ISSN 1424-8220, Vol. 21, no 17, article id 5932Article in journal (Refereed)
    Abstract [en]

    Monitoring core body temperature (Tc) during training and competitions, especially in a hot environment, can help enhance an athlete’s performance, as well as lower the risk for heat stroke. Accordingly, a noninvasive sensor that allows reliable monitoring of Tc would be highly beneficial in this context. One such novel non-invasive sensor was recently introduced onto the market (CORE, greenTEG, Rümlang, Switzerland), but, to our knowledge, a validation study of this device has not yet been reported. Therefore, the purpose of this study was to evaluate the validity and reliability of the CORE sensor. In Study I, 12 males were subjected to a low-to-moderate heat load by performing, on two separate occasions several days apart, two identical 60-min bouts of steady-state cycling in the laboratory at 19 °C and 30% relative humidity. In Study II, 13 males were subjected to moderate-to-high heat load by performing 90 min of cycling in the laboratory at 31 °C and 39% relative humidity. In both cases the core body temperatures indicated by the CORE sensor were compared to the corresponding values obtained using a rectal sensor (Trec). The first major finding was that the reliability of the CORE sensor is acceptable, since the mean bias between the two identical trials of exercise (0.02 °C) was not statistically significant. However, under both levels of heat load, the body temperature indicated by the CORE sensor did not agree well with Trec, with approximately 50% of all paired measurements differing by more than the predefined threshold for validity of ≤0.3 °C. In conclusion, the results obtained do not support the manufacturer’s claim that the CORE sensor provides a valid measure of core body temperature.

  • 67.
    Wan, Jiafu
    et al.
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    Liu, Jianqi
    School of Information Engineering, Guangdong Mechanical & Electrical College, Guangzhou.
    Shao, Zehio
    School of Information Science and Technology, Chengdu University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Imran, Muhammad Al
    College of Computer and Information Sciences, Almuzahmiyah, King Saud University.
    Zhou, Keliang
    School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou.
    Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles2016In: Sensors, E-ISSN 1424-8220, Vol. 16, no 1, article id 88Article in journal (Refereed)
    Abstract [en]

    The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction.

  • 68.
    Wang, Qiu
    et al.
    Faculty of Information Technology, Macau University of Science and Technology, Macau.
    Dai, Hong-Ning
    Faculty of Information Technology, Macau University of Science and Technology, Macau.
    Zheng, Zibin
    School of Data and Computer Science, Sun Yat-Sen University, Guangzhou .
    Imran, Muhammad
    College of Computer and Information Sciences, King Saud University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    On Connectivity of Wireless Sensor Networks with Directional Antennas2017In: Sensors, E-ISSN 1424-8220, Vol. 17, no 1, article id E134Article in journal (Refereed)
    Abstract [en]

    In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.

  • 69.
    Xiong, Naixue
    et al.
    Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK .
    Zhang, Longzhen
    School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai.
    Zhang, Wei
    Department of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Imran, Muhammad
    College of Computer and Information Sciences, King Saud University.
    Design and Analysis of an Efficient Energy Algorithm in Wireless Social Sensor Networks2017In: Sensors, E-ISSN 1424-8220, Vol. 17, no 10, article id 2166Article in journal (Refereed)
    Abstract [en]

    Because mobile ad hoc networks have characteristics such as lack of center nodes, multi-hop routing and changeable topology, the existing checkpoint technologies for normal mobile networks cannot be applied well to mobile ad hoc networks. Considering the multi-frequency hierarchy structure of ad hoc networks, this paper proposes a hybrid checkpointing strategy which combines the techniques of synchronous checkpointing with asynchronous checkpointing, namely the checkpoints of mobile terminals in the same cluster remain synchronous, and the checkpoints in different clusters remain asynchronous. This strategy could not only avoid cascading rollback among the processes in the same cluster, but also avoid too many message transmissions among the processes in different clusters. What is more, it can reduce the communication delay. In order to assure the consistency of the global states, this paper discusses the correctness criteria of hybrid checkpointing, which includes the criteria of checkpoint taking, rollback recovery and indelibility. Based on the designed Intra-Cluster Checkpoint Dependence Graph and Inter-Cluster Checkpoint Dependence Graph, the elimination rules for different kinds of checkpoints are discussed, and the algorithms for the same cluster checkpoints, different cluster checkpoints, and rollback recovery are also given. Experimental results demonstrate the proposed hybrid checkpointing strategy is a preferable trade-off method, which not only synthetically takes all kinds of resource constraints of Ad hoc networks into account, but also outperforms the existing schemes in terms of the dependence to cluster heads, the recovery time compared to the pure synchronous, and the pure asynchronous checkpoint advantage.

  • 70.
    Zuo, Yang
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lundberg, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Najeh, Taoufik
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Rantatalo, Matti
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Odelius, Johan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Squat Detection of Railway Switches and Crossings Using Point Machine Vibration Measurements2023In: Sensors, E-ISSN 1424-8220, Vol. 23, no 7, article id 3666Article in journal (Refereed)
    Abstract [en]

    Railway switches and crossings (S&C) are among the most important high-value components in a railway network and a failure of such an asset could result in severe network disturbance. Therefore, potential defects need to be detected at an early stage to prevent traffic-disturbing downtime or even severe accidents. A squat is a common defect of S&Cs that has to be monitored and repaired to reduce such risks. In this study, a testbed including a full-scale S&C and a bogie wagon was developed. Vibrations were measured for different squat sizes by an accelerometer mounted at the point machine. A method of processing the vibration data and the speed data is proposed to investigate the possibility of detecting and quantifying the severity of a squat. One key technology used is wavelet denoising. The study shows that it is possible to monitor the development of the squat size on the rail up to around 13 m from the point machine. The relationships between the normalised peak-to-peak amplitude of the vibration signal and the squat depth were also estimated.

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  • 71.
    Zuo, Yang
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thiery, Florian
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Chandran, Praneeth
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Odelius, Johan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Rantatalo, Matti
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Squat Detection of Railway Switches and Crossings Using Wavelets and Isolation Forest2022In: Sensors, E-ISSN 1424-8220, Vol. 22, no 17, article id 6357Article in journal (Refereed)
    Abstract [en]

    Railway switches and crossings (S&Cs) are critical, high-value assets in railway networks. A single failure of such an asset could result in severe network disturbance and considerable economical losses. Squats are common rail surface defects of S&Cs and need to be detected and estimated at an early stage to minimise maintenance costs and increase the reliability of S&Cs. For practicality, installation of wired or wireless sensors along the S&C may not be reliable due to the risk of damages of power and signal cables or sensors. To cope with these issues, this study presents a method for collecting and processing vibration data from an accelerometer installed at the point machine to extract features related to the squat defects of the S&C. An unsupervised anomaly-detection method using the isolation forest algorithm is applied to generate anomaly scores from the features. Important features are ranked and selected. This paper describes the procedure of parameter tuning and presents the achieved anomaly scores. The results show that the proposed method is effective and that the generated anomaly scores indicate the health status of an S&C regarding squat defects.

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